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  • 来自专栏绿巨人专栏

    Represent code in math equations

    Introduce The article shows a way to use math equations to represent code's logical.

    72870发布于 2018-05-16
  • 【HDU】2266 - How Many Equations Can You Find(dfs)

    点击打开题目 How Many Equations Can You Find Time Limit: 2000/1000 MS (Java/Others) Memory Limit: 32768

    19610编辑于 2025-08-27
  • 来自专栏懒人开发

    (10.1)James Stewart Calculus 5th Edition:Curves Defined by Parametric Equations

    ---- Curves Defined by Parametric Equations 曲线定义的参数方程 有的时候,有些曲线不符合 the Vertical Line Test 竖线检测 例如: ? 虽然不能写成 y = f(x) 但是,他们都是 时间 t 的 函数: 假如 x,y都是 第3个参数 t 的函数, 即: x = f(t) , y = g(t) 被叫做 parametric equations

    1.2K10发布于 2018-09-12
  • 来自专栏懒人开发

    (9.1)James Stewart Calculus 5th Edition:Modeling with Differential Equations

    ---- General Differential Equations 一般微分方程 In general, a differential equation is an equation that contains

    84040发布于 2018-09-12
  • 来自专栏AI科技评论

    学界 | NIPS2018最佳论文解读:Neural Ordinary Differential Equations

    AI 科技评论按:不久前,NeurIPS 2018 在加拿大蒙特利尔召开,在这次著名会议上获得最佳论文奖之一的论文是《Neural Ordinary Differential Equations》,论文地址 来源:https://towardsdatascience.com/paper-summary-neural-ordinary-differential-equations-37c4e52df128

    3.1K20发布于 2019-01-09
  • 来自专栏数据驱动实践

    ggplot2拓展功能:添加拟合公式(Equations, R2, BIC, AIC etc.)

    Fit polynomial equation: Create some data: set.seed(4321) x <- 1:100 y <- (x + x^2 + x^3) + rnorm(length(x), mean = 0, sd = mean(x^3) / 4) my.data <- data.frame(x, y, group = c("A", "B"), y2 = y * c(0.5,2), block = c("a", "a", "b", "b")) Fit polynomial regression line and add labels: # Polynomial regression. Sow equation and adjusted R2 formula <- y ~ poly(x, 3, raw = TRUE) p <- ggplot(my.data, aes(x, y2, color = group)) + geom_point() + geom_smooth(aes(fill = group), method = "lm", formula = formula) + stat_poly_eq( aes(label = paste(..eq.label.., ..adj.rr.label.., sep = "~~~~")), formula = formula, parse = TRUE ) ggpar(p, palette = "jco")

    6.3K10发布于 2020-11-04
  • 来自专栏Reck Zhang

    LeetCode 0399 - Evaluate Division

    (); i++) { father[equations[i][0]] = equations[i][0]; father[equations[i][1]] = equations[i][1]; pairs[equations[i][0]].insert({equations[i][1], values[i]}); pairs[equations[i][1]].insert({equations[i][0], 1.0f / values[i]}); } for(unsigned long long i = 0; i < equations.size(); i++) { auto a = find(equations[i][0]); auto b = find(equations[i][1]); if(a !

    35840发布于 2021-08-11
  • 来自专栏前端小书童

    一天一大 leet (990. 等式方程的可满足性)

    =z"] 输出:true 提示 1 <= equations.length <= 500 equations[i].length == 4 equations[i][0] 和 equations[i] equations[i][2] 是 '=' 抛砖引玉 ? ; index++) { if (equations[index][1] === '=') { var index1 = equations[index].charCodeAt(0) } } for (var index = 0; index < equations.length; index++) { if (equations[index][1] === '!') { var index1 = equations[index].charCodeAt(0) - 97 var index2 = equations[index].charCodeAt

    43220发布于 2020-09-24
  • 来自专栏Michael阿明学习之路

    LeetCode 990. 等式方程的可满足性(并查集)

    =z"] 输出:true 提示: 1 <= equations.length <= 500 equations[i].length == 4 equations[i][0] 和 equations[ i][3] 是小写字母 equations[i][1] 要么是 '=',要么是 '!' equations[i][2] 是 '=' 来源:力扣(LeetCode) 链接:https://leetcode-cn.com/problems/satisfiability-of-equality-equations if(equations[i][1]=='=') { a = equations[i][0]-'a'; b = equations { a = equations[i][0]-'a'; b = equations[i][3]-'a'; if

    59730发布于 2020-07-13
  • 来自专栏Michael阿明学习之路

    LeetCode 399. 除法求值(图的DFS搜索)

    返回 [6.0, 0.5, -1.0, 1.0, -1.0 ] 输入为: vector<pair<string, string>> equations, vector<double>& values 基于上述例子,输入如下: equations(方程式) = [ ["a", "b"], ["b", "c"] ], values(方程式结果) = [2.0, 3.0], queries(问题方程式) , vector<double>& values, vector<vector<string>>& queries) { for(int i = 0; i < equations.size (); ++i) { m[equations[i][0]][equations[i][1]] = values[i];//正向 m[equations [i][1]][equations[i][0]] = 1.0/values[i];//反向 } ans.resize(queries.size()); for

    59720发布于 2020-07-13
  • 来自专栏leetcode题目解析和知识分享

    并查集-990.等式方程的可满足性-力扣(LeetCode)

    个人主页:1白天的黑夜1-CSDN博客 专栏:力扣刷题录_1白天的黑夜1的博客-CSDN博客、企鹅程序员:Linux 系统与网络编程_1白天的黑夜1的博客-CSDN博客 一、题目解析 1、1 <= equations.length <= 500 2、equations[i].length == 4 3、equations[i][0] 和 equations[i][3] 是小写字母 4、equations[i][1] 要么是 '= 5、equations[i][2] 是 '=' 二、算法原理 对并查集陌生的读者,可以移步另一篇博客学习或者回顾一下 高阶数据结构-并查集-CSDN博客 我们可以看到题目中的一句话,“只有当可以将整数分配给变量名 ) { UnionFindSet ufs(26); //相等的放在同一个集合中 for(auto& str : equations) 0) x = ufs[x]; return x; }; //第一先把相等的值加到一个集合中 for(auto& str : equations

    17310编辑于 2025-10-22
  • 来自专栏X

    Leetcode|并查集|990. 等式方程的可满足性

    ) { int size = equations.size(); UnionFind uf(26); // 26个字母,作为26个节点 // 先对等式进行建树 for (int i = 0; i < size; i++) { if (equations[i][1] == '=') uf.unite (equations[i][0] - 'a', equations[i][3] - 'a'); } // 不等式拿来检查连通性,若连通,则等式不成立,反之成立 for (int i = 0; i < size; i++) { if (equations[i][1] == '!') if (uf.connected(equations[i][0] - 'a', equations[i][3] - 'a')) return false; } return

    31810发布于 2021-09-22
  • 来自专栏C++/Linux

    【数据结构】并查集

    等式方程的可满足性 题目:给定一个由表示变量之间关系的字符串方程组成的数组,每个字符串方程 equations[i] 的长度为 4,并采用两种不同的形式之一:“a==b” 或 “a!=b”。 =z”] 输出:true 提示: 1 <= equations.length <= 500 equations[i].length == 4 equations[i][0] 和 equations[i ][3] 是小写字母 equations[i][1] 要么是 ‘=’,要么是 ‘!’ equations[i][2] 是 ‘=’ 思路:因为只是对小写字母之间判断是否有相悖的结论,所以我们可以先遍历一遍,将所有相等的放入一个并查集中;然后第二次遍历就找不相等的,如果这两个不相等的元素出现在并查集中 false;否则返回 true;代码如下: class Solution { public: bool equationsPossible(vector<string>& equations

    45310编辑于 2024-03-09
  • 来自专栏眯眯眼猫头鹰的小树杈

    leetcode399. Evaluate Division

    题目要求 Equations are given in the format A / B = k, where A and B are variables represented as strings, The input is: vector<pair<string, string>> equations, vector<double>& values, vector<pair<string, string >> queries , where equations.size() == values.size(), and the values are positive. This represents the equations. Return vector<double>. According to the example above: equations = [ ["a", "b"], ["b", "c"] ], values = [2.0, 3.0], queries

    57320发布于 2019-07-02
  • 来自专栏OpenFPGA

    ‘SHIT’上最全有限状态机设计研究(四)-时钟同步状态机设计1

    第四步,Choose flip-flop type, construct excitation equations (选择触发器类型,构造激励方程) ? output table(构造状态表) State assignment(状态分配) Create transition/output table(转移/输出表) Derive transition equations and output equations (导出转移方程和输出方程) Choose flip-flop, Construct excitation equations (选择触发器,构造激励方程)

    94410发布于 2020-06-30
  • 来自专栏计算机视觉理论及其实现

    除法求值\

    给你一个变量对数组 equations 和一个实数值数组 values 作为已知条件,其中 equations[i] = [Ai, Bi] 和 values[i] 共同表示等式 Ai / Bi = values 构图 根据上面的分析,我们可以根据输入 equations[i] = [Ai, Bi] 和 values[i] 共同表示等式 Ai / Bi = values[i] 进行构图: 构建一条从 Ai 节点 class Solution { public:     vector<double> calcEquation(vector<vector<string>>& equations, vector<double / 生成存储变量所构成的图结构         unordered_map<string, unordered_map<string, double>> graph;         int n = equations.size ();           for(int i = 0; i < n; i++){             string s = equations[i][0], e = equations[i][1]

    86010编辑于 2023-11-27
  • 来自专栏健程之道

    力扣399——除法求值

    返回 [6.0, 0.5, -1.0, 1.0, -1.0 ] 输入为: vector<pair<string, string>> equations, vector<double> values, 其中 equations.size() == values.size(),即方程式的长度与方程式结果长度相等(程式与结果一一对应),并且结果值均为正数。以上为方程式的描述。 基于上述例子,输入如下: equations(方程式) = [ ["a", "b"], ["b", "c"] ], values(方程式结果) = [2.0, 3.0], queries(问题方程式) 利用递归的话,可以很好写出代码,我提供一个 DFS 的例子: class Solution { public double[] calcEquation(List<List<String>> equations (); i++) { union(equations.get(i).get(0), equations.get(i).get(1), values[i]); }

    53610发布于 2020-02-19
  • 来自专栏CSDN旧文

    数学--数论--HDU 1299 +POJ 2917 Diophantus of Alexandria (因子个数函数+公式推导)

    He was one of the first mathematicians to study equations where variables were restricted to integral In honor of him, these equations are commonly called diophantine equations.

    69930发布于 2020-11-03
  • 来自专栏TechFlow

    LeetCode专题】Evaluate Division

    在双向连接图中进行DFS时需要记录一下已经到达过的节点,不然会陷入无限循环之中,以下是完整的python代码: class Solution(object): def calcEquation(self, equations , values, queries): """ :type equations: List[List[str]] :type values: List[float construct a bi-directional graph with a nested dict graph = dict() for idx in range(0, len(equations )): equation = equations[idx] numerator = equation[0] denominator

    56910发布于 2020-03-05
  • 来自专栏云深之无迹

    Python绘制动图

    matplotlib.animation as animation g = 9.8 leng = 1.0 b_const = 0.2 # no decay case: def pendulum_equations1 = w dth = v dv = - g/l * sin(th) return dth, dv # the decay exist case: def pendulum_equations2 dv = -b/l * v - g/l * sin(th) return dth, dv t = np.arange(0, 20, 0.1) track = odeint(pendulum_equations1 , (1.0, 0), t, args=(leng,)) #track = odeint(pendulum_equations2, (1.0, 0), t, args=(leng, b_const))

    82070发布于 2021-05-18
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